R/zchunk_L201.en_nonco2.R
In bpbond/gcamdata: Build the GCAM Input Datasets
Defines functions
module_emissions_L201.en_nonco2
Documented in
module_emissions_L201.en_nonco2
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_emissions_L201.en_nonco2
#'
#' Generate non-CO2 emissions: pollutants, GHGs, non-CO2, BC/OCs, and reduction data.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{L201.en_pol_emissions}, \code{L201.en_ghg_emissions}, \code{L201.en_bcoc_emissions}, \code{L201.OutputEmissions_elec}, \code{L201.nonghg_max_reduction}, \code{L201.nonghg_steepness}, \code{L201.nonghg_max_reduction_res}, \code{L201.nonghg_steepness_res}, \code{L201.nonghg_res}, \code{L201.ghg_res}, \code{L201.ResReadInControl_nonghg_res}, \code{L201.ResReadInControl_ghg_res}. The corresponding file in the
#' original data system was \code{L201.en_nonco2.R} (emissions level2).
#' @details Set up all of the inputs needed for the energy system non-CO2 emissions in GCAM.
#' This includes historical emissions, drivers (input or output), and pollution controls.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter full_join left_join mutate pull select
#' @importFrom tidyr gather
#' @author BBL July 2017
module_emissions_L201.en_nonco2 <- function(command, ...) {
UCD_tech_map_name <- if_else(energy.TRAN_UCD_MODE == 'rev.mode', "energy/mappings/UCD_techs_revised", "energy/mappings/UCD_techs")
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "emissions/mappings/ind_subsector_revised",
FILE = "energy/A_regions",
"L111.nonghg_tg_R_en_S_F_Yh",
"L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L112.ghg_tg_R_en_S_F_Yh",
"L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L114.bcoc_tgej_R_en_S_F_2000",
"L151.nonghg_ctrl_R_en_S_T",
FILE = "emissions/A51.steepness",
"L244.DeleteThermalService",
# the following to be able to map in the input.name to
# use for the input-driver
FILE = "energy/calibrated_techs",
FILE = "energy/calibrated_techs_bld_det",
FILE = UCD_tech_map_name))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L201.en_pol_emissions",
"L201.en_ghg_emissions",
"L201.en_bcoc_emissions",
"L201.OutputEmissions_elec",
"L201.nonghg_max_reduction",
"L201.nonghg_steepness",
"L201.nonghg_max_reduction_res",
"L201.nonghg_steepness_res",
"L201.nonghg_res",
"L201.ghg_res",
"L201.ResReadInControl_nonghg_res",
"L201.ResReadInControl_ghg_res"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
year <- value <- supplysector <- region <- subsector <- subsector.emissions <- subsector.original<- stub.technology <- Non.CO2 <-
input.emissions <- `2000` <- emiss.coef <- ctrl.name <- max_reduction <- variable <-
steepness <- SO2 <- NOx <- CO <- BC <- OC <- NMVOC <- resource <- has_district_heat <-
. <- region <- supplysector <- max.reduction <- technology <- minicam.energy.input <-
tranSubsector <- tranTechnology <- input.name <- efficiency <- fuel <- subsector_orig <- NULL # silence package check notes
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A_regions <- get_data(all_data, "emissions/A_regions")
A_regions.en <- get_data(all_data, "energy/A_regions")
ind_subsector_revised <- get_data(all_data,"emissions/mappings/ind_subsector_revised")
L111.nonghg_tg_R_en_S_F_Yh <- get_data(all_data, "L111.nonghg_tg_R_en_S_F_Yh", strip_attributes = TRUE)
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP <- get_data(all_data, "L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP", strip_attributes = TRUE)
L112.ghg_tg_R_en_S_F_Yh <- get_data(all_data, "L112.ghg_tg_R_en_S_F_Yh", strip_attributes = TRUE)
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP <- get_data(all_data, "L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP", strip_attributes = TRUE)
L114.bcoc_tgej_R_en_S_F_2000 <- get_data(all_data, "L114.bcoc_tgej_R_en_S_F_2000", strip_attributes = TRUE)
L151.nonghg_ctrl_R_en_S_T <- get_data(all_data, "L151.nonghg_ctrl_R_en_S_T", strip_attributes = TRUE)
A51.steepness <- get_data(all_data, "emissions/A51.steepness", strip_attributes = TRUE)
L244.DeleteThermalService <- get_data(all_data, "L244.DeleteThermalService", strip_attributes = TRUE)
# make a complete mapping to be able to look up with sector + subsector + tech the
# input name to use for an input-driver
bind_rows(
get_data(all_data, "energy/calibrated_techs") %>% select(supplysector, subsector, fuel, technology, minicam.energy.input),
get_data(all_data, "energy/calibrated_techs_bld_det") %>% select(supplysector, subsector, fuel, technology, minicam.energy.input),
get_data(all_data, UCD_tech_map_name) %>% select(supplysector, subsector = tranSubsector, fuel, technology = tranTechnology, minicam.energy.input)) %>%
left_join(ind_subsector_revised %>% select(supplysector, subsector.emissions, fuel, technology, minicam.energy.input),
by=c("supplysector","fuel","technology","minicam.energy.input")) %>% #remap iron and steel subsector to match emissions data
mutate(subsector = if_else(!is.na(subsector.emissions),subsector.emissions,subsector)) %>%
select(-subsector.emissions)%>%
rename(stub.technology = technology,
input.name = minicam.energy.input) %>%
distinct() ->
EnTechInputNameMap
# L201.en_pol_emissions: Pollutant emissions for energy technologies in all regions
L111.nonghg_tg_R_en_S_F_Yh %>%
filter(supplysector != "out_resources",
year %in% emissions.MODEL_BASE_YEARS) %>%
# add region name and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(EnTechInputNameMap,by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, input.emissions = value, Non.CO2, input.name) %>%
mutate(input.emissions = signif(input.emissions, emissions.DIGITS_EMISSIONS)) ->
L201.en_pol_emissions
# L201.en_ghg_emissions: GHG emissions for energy technologies in all regions
L112.ghg_tg_R_en_S_F_Yh %>%
filter(supplysector != "out_resources",
year %in% emissions.MODEL_BASE_YEARS) %>%
# add region name and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(EnTechInputNameMap,by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, input.emissions = value, Non.CO2, input.name) %>%
mutate(input.emissions = signif(input.emissions, emissions.DIGITS_EMISSIONS)) ->
L201.en_ghg_emissions
# Add back in correct subsector name for iron and steel sector
L201.en_pol_emissions %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original, technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
L201.en_pol_emissions
L201.en_ghg_emissions %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original, technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
L201.en_ghg_emissions
EnTechInputNameMap %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original,fuel,technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "fuel","stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
EnTechInputNameMap
# L201.en_bcoc_emissions: BC/OC emissions factors for energy technologies in all regions
L114.bcoc_tgej_R_en_S_F_2000 %>%
filter(supplysector != "out_resources") %>%
# add region name, extend emissions factors across all base years, and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
repeat_add_columns(tibble(year = MODEL_BASE_YEARS)) %>%
left_join_error_no_match(EnTechInputNameMap, by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, emiss.coef = `2000`, Non.CO2, input.name) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.en_bcoc_emissions
# Convert electricity to use output-driver instead. We do this, despite the addional hoops, because it makes it
# easier to swap out a different structure for electricity which requires pass-through technologies such as to
# add cooling technologies
# L201.OutputEmissions_elec: processing is straightforward here, just move electricity rows out of the InputEmissions
# table into the OutputEmissions
bind_rows(filter(L201.en_pol_emissions, supplysector == "electricity"),
filter(L201.en_ghg_emissions, supplysector == "electricity")) %>%
select(LEVEL2_DATA_NAMES[["OutputEmissions"]]) ->
L201.OutputEmissions_elec
L201.en_pol_emissions <- filter(L201.en_pol_emissions, supplysector != "electricity")
L201.en_ghg_emissions <- filter(L201.en_ghg_emissions, supplysector != "electricity")
L201.en_bcoc_emissions <- filter(L201.en_bcoc_emissions, supplysector != "electricity")
# L201.nonghg_max_reduction: maximum reduction for energy technologies in all regions
L151.nonghg_ctrl_R_en_S_T %>%
filter(supplysector != "out_resources") %>%
# add region name
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
select(-year)->L201.max_reduction
L201.max_reduction %>%
# select only certain columns in preparation for join below
select(region, supplysector, subsector, stub.technology, Non.CO2) %>%
mutate(year = emissions.CTRL_BASE_YEAR, ctrl.name = "GDP_control") %>%
left_join_error_no_match(L201.max_reduction,
by = c("region", "supplysector", "subsector", "stub.technology", "Non.CO2")) %>%
na.omit %>%
select(region, supplysector, subsector, stub.technology, year, Non.CO2, ctrl.name, max_reduction) ->
L201.nonghg_max_reduction
# L201.nonghg_steepness: steepness of reduction for energy technologies in all regions
A51.steepness %>%
gather(variable, steepness, SO2, NOx, CO, BC, OC, NMVOC) %>%
filter(supplysector != "out_resources") %>%
# extend steepness factors across all regions
repeat_add_columns(tibble(region = GCAM_region_names$region)) ->
L201.steepness
L201.nonghg_max_reduction %>%
mutate(year = emissions.CTRL_BASE_YEAR, ctrl.name = "GDP_control") %>%
left_join(L201.steepness,
by = c("region", "supplysector", "subsector", "stub.technology", "Non.CO2" = "variable")) %>%
na.omit %>%
select(region, supplysector, subsector, stub.technology, year, Non.CO2, ctrl.name, steepness) ->
L201.nonghg_steepness
# Remove rows where we only have a value for one of max.reduction or steepness
# TODO: is this what we want or should we raise an error? [from original code]
L201.nonghg_max_reduction %>%
full_join(L201.nonghg_steepness,
by = c("region", "supplysector", "subsector", "stub.technology", "year", "Non.CO2", "ctrl.name")) %>%
na.omit %>%
# No need to include a GDP control when the max.reduction is zero
filter(max_reduction > 0) ->
L201.nonghg_gdp_control
# remap iron and steel back to correct subsector, because fuel information is now attached
L201.nonghg_gdp_control %>%
left_join(EnTechInputNameMap %>% filter(supplysector == "iron and steel") %>% select(-input.name) %>%
rename(subsector_orig = subsector) %>% unique(),
by = c("supplysector", "stub.technology")) %>%
mutate(subsector = if_else(supplysector == "iron and steel", subsector_orig, subsector)) %>%
select(-subsector_orig) ->
L201.nonghg_gdp_control
L201.nonghg_max_reduction <- select(L201.nonghg_gdp_control, -steepness)
L201.nonghg_steepness <- select(L201.nonghg_gdp_control, -max_reduction)
# L201.nonghg_res: Pollutant emissions for energy resources in all regions
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
filter(supplysector == "out_resources",
year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector) %>%
rename(subresource = subsector, technology = stub.technology, emiss.coef = value) %>%
select(LEVEL2_DATA_NAMES[["ResEmissCoef"]]) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.nonghg_res
# L201.ghg_res: GHG emissions from resource production in all regions
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
filter(supplysector == "out_resources",
year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector) %>%
rename(subresource = subsector, technology = stub.technology, emiss.coef = value) %>%
select(LEVEL2_DATA_NAMES[["ResEmissCoef"]]) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.ghg_res
# Resources have vintaging going on in the historical years.
# The above emissions coefficients are the coefficients across vintages
# in the given model year. The best way to ensure the correct "total"
# emissions factor across vintages is realized is to use the ReadInControl
# to change the coefficients by vintage for all vintages. Note given the way
# the C++ operates we need to read in the "base" EmissCoef table and then the
# same values in the ReadInControl table all read into the first model period
# vintage. We will also need to "fillout" the value in the final calibration
# to the future model periods otherwise the vintage would revert back to the
# value in the EmissCoef table. Finally to turn "off" any adjustments made to
# new vintages in future model periods we must have ReadInControl with values of
# zero starting in the first future model period.
# L201.ResReadInControl_nonghg_res: Vintage adjustments for Pollutant emissions for energy resources in all regions
L201.nonghg_res %>%
# copy the final historical year value to the future model periods
bind_rows(L201.nonghg_res %>%
filter(year == MODEL_FINAL_BASE_YEAR) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS))) %>%
rename(future.emiss.coeff.year = year) %>%
mutate(year = MODEL_BASE_YEARS[1],
future.emiss.coeff.name = "vintage_adjust") %>%
select(LEVEL2_DATA_NAMES[["ResReadInControl"]]) ->
L201.ResReadInControl_nonghg_res
# turn "off" vintage adjustments for future year vintages
L201.ResReadInControl_nonghg_res %>%
mutate(year = MODEL_FUTURE_YEARS[1],
emiss.coef = 0.0) %>%
bind_rows(L201.ResReadInControl_nonghg_res) ->
L201.ResReadInControl_nonghg_res
# L201.ResReadInControl_ghg_res: Vintage adjustments for GHG emissions from resource production in all regions
L201.ghg_res %>%
# copy the final historical year value to the future model periods
bind_rows(L201.ghg_res %>%
filter(year == MODEL_FINAL_BASE_YEAR) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS))) %>%
rename(future.emiss.coeff.year = year) %>%
mutate(year = MODEL_BASE_YEARS[1],
future.emiss.coeff.name = "vintage_adjust") %>%
select(LEVEL2_DATA_NAMES[["ResReadInControl"]]) ->
L201.ResReadInControl_ghg_res
# turn "off" vintage adjustments for future year vintages
L201.ResReadInControl_ghg_res %>%
mutate(year = MODEL_FUTURE_YEARS[1],
emiss.coef = 0.0) %>%
bind_rows(L201.ResReadInControl_ghg_res) ->
L201.ResReadInControl_ghg_res
# L201.nonghg_max_reduction_res: maximum reduction for resources in all regions
L151.nonghg_ctrl_R_en_S_T %>%
filter(supplysector == "out_resources") %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector,
year = emissions.GHG_CONTROL_READIN_YEAR,
ctrl.name = "GDP_control") %>%
rename(subresource = subsector, technology = stub.technology, max.reduction = max_reduction) %>%
select(LEVEL2_DATA_NAMES[["GDPCtrlMaxRes"]]) ->
L201.nonghg_max_reduction_res
# L201.nonghg_steepness_res: steepness of reduction for resources in all regions
A51.steepness %>%
gather(Non.CO2, value, SO2, NOx, CO, BC, OC, NMVOC) %>%
filter(supplysector == "out_resources") %>%
# extend steepness factors across all regions
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(resource = subsector,
year = emissions.GHG_CONTROL_READIN_YEAR,
ctrl.name = "GDP_control") %>%
rename(subresource = subsector, technology = stub.technology, steepness = value) %>%
select(LEVEL2_DATA_NAMES[["GDPCtrlSteepRes"]]) ->
L201.nonghg_steepness_res
# Remove rows where we only have a value for one of max.reduction or steepness
# TODO: is this what we want or should we raise an error?
L201.nonghg_max_reduction_res %>%
full_join(L201.nonghg_steepness_res, by = c("region", "resource", "subresource", "technology", "year", "Non.CO2", "ctrl.name")) %>%
na.omit %>%
# No need to include a GDP control when the max.reduction is zero
filter(max.reduction > 0) ->
L201.nonghg_gdp_control_res
L201.nonghg_max_reduction_res <- select(L201.nonghg_gdp_control_res, -steepness)
L201.nonghg_steepness_res <- select(L201.nonghg_gdp_control_res, -max.reduction)
# Rename to regional SO2
L201.en_pol_emissions <- rename_SO2(L201.en_pol_emissions, A_regions, FALSE)
L201.OutputEmissions_elec <- rename_SO2(L201.OutputEmissions_elec, A_regions, FALSE)
L201.nonghg_max_reduction <- rename_SO2(L201.nonghg_max_reduction, A_regions, FALSE)
L201.nonghg_steepness <- rename_SO2(L201.nonghg_steepness, A_regions, FALSE)
L201.nonghg_res <- rename_SO2(L201.nonghg_res, A_regions, FALSE)
L201.ResReadInControl_nonghg_res <- rename_SO2(L201.ResReadInControl_nonghg_res, A_regions, FALSE)
L201.nonghg_steepness_res <- rename_SO2(L201.nonghg_steepness_res, A_regions, FALSE)
L201.nonghg_max_reduction_res <- rename_SO2(L201.nonghg_max_reduction_res, A_regions, FALSE)
# Remove district heat from regions that do have have it
A_regions.en %>%
filter(has_district_heat == 1) %>%
pull(region) ->
distheat.regions
L201.en_pol_emissions <- filter(L201.en_pol_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.en_ghg_emissions <- filter(L201.en_ghg_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.en_bcoc_emissions <- filter(L201.en_bcoc_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.nonghg_max_reduction <- filter(L201.nonghg_max_reduction, supplysector != "district heat" | region %in% distheat.regions)
L201.nonghg_steepness <- filter(L201.nonghg_steepness, supplysector != "district heat" | region %in% distheat.regions)
# It may be the case with certain regional aggregations that regions exist that have no
# heating or cooling sectors. We should delete those here.
# Delete sectors that do not exist due to zero heating/cooling degree days
delete_nonexistent_sectors <- function(x, L201.delete.sectors) {
filter(x, ! paste0(region, supplysector) %in% L201.delete.sectors)
}
L201.delete.sectors <- paste0(L244.DeleteThermalService$region, L244.DeleteThermalService$supplysector)
L201.en_pol_emissions <- delete_nonexistent_sectors(L201.en_pol_emissions, L201.delete.sectors)
L201.en_ghg_emissions <- delete_nonexistent_sectors(L201.en_ghg_emissions, L201.delete.sectors)
L201.en_bcoc_emissions <- delete_nonexistent_sectors(L201.en_bcoc_emissions, L201.delete.sectors)
L201.nonghg_max_reduction <- delete_nonexistent_sectors(L201.nonghg_max_reduction, L201.delete.sectors)
L201.nonghg_steepness <- delete_nonexistent_sectors(L201.nonghg_steepness, L201.delete.sectors)
# Produce outputs
L201.en_pol_emissions %>%
add_title("Pollutant emissions for energy technologies in all regions") %>%
add_units("Tg") %>%
add_comments("Take non-GHG emissions for the energy system, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_pol_emissions") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L111.nonghg_tg_R_en_S_F_Yh",
"L244.DeleteThermalService",
"emissions/mappings/ind_subsector_revised") ->
L201.en_pol_emissions
L201.en_ghg_emissions %>%
add_title("GHG emissions for energy technologies in all regions") %>%
add_units("Tg") %>%
add_comments("Take GHG emissions for the energy system, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_ghg_emissions") %>%
add_precursors("common/GCAM_region_names",
"energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L112.ghg_tg_R_en_S_F_Yh",
"L244.DeleteThermalService",
"emissions/mappings/ind_subsector_revised") ->
L201.en_ghg_emissions
L201.en_bcoc_emissions %>%
add_title("BC/OC emissions factors for energy technologies in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take BC/OC emissions factors for energy technologies, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_bcoc_emissions") %>%
add_precursors("common/GCAM_region_names",
"energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L114.bcoc_tgej_R_en_S_F_2000",
"L244.DeleteThermalService") ->
L201.en_bcoc_emissions
L201.OutputEmissions_elec %>%
add_title("GHG and pollutant emissions for the electricity sector") %>%
add_units("Tg") %>%
add_comments("We've seperated electricity out to be driven by output-driver so we") %>%
add_comments("more easily re-configure the strucutre of the sector to swap in cooling") %>%
add_comments("technology choice which is implemented with pass-through sector/tech") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L111.nonghg_tg_R_en_S_F_Yh") ->
L201.OutputEmissions_elec
L201.nonghg_max_reduction %>%
rename(max.reduction = max_reduction) %>% # no idea why old data system renamed this
add_title("Maximum emissions reduction rates for energy technologies in all regions") %>%
add_units("%") %>%
add_comments("The maximum reduction is calculated in L151 to match the maximum emissions controls assumed in GCAM3.") %>%
add_comments("Controls are removed when the maximum reduction is zero.") %>%
add_legacy_name("L201.nonghg_max_reduction") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L151.nonghg_ctrl_R_en_S_T",
"L244.DeleteThermalService") ->
L201.nonghg_max_reduction
L201.nonghg_steepness %>%
add_title("Steepness of emissions reduction for energy technologies in all regions") %>%
add_units("%") %>%
add_comments("The steepness is from an assumptions file (A51_steepness). It was chosen to replicate the pollutant reduction rates for SO2 in GCAM3.") %>%
add_comments("Steepness is removed for technologies with maximum reduction rates of 0.") %>%
add_legacy_name("L201.nonghg_steepness") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L151.nonghg_ctrl_R_en_S_T",
"emissions/A51.steepness",
"L244.DeleteThermalService") ->
L201.nonghg_steepness
L201.nonghg_max_reduction_res %>%
add_title("Maximum reduction for resources in all regions") %>%
add_units("%") %>%
add_comments("The maximum reduction is calculated in L151 to match the maximum emissions controls assumed in GCAM3.") %>%
add_comments("Controls are removed when the maximum reduction is zero.") %>%
add_legacy_name("L201.nonghg_max_reduction_res") %>%
same_precursors_as(L201.nonghg_max_reduction) ->
L201.nonghg_max_reduction_res
L201.nonghg_steepness_res %>%
add_title("Steepness of reduction for resources in all regions") %>%
add_units("%") %>%
add_comments("The steepness is from an assumptions file (A51_steepness). It was chosen to replicate the pollutant reduction rates for SO2 in GCAM3.") %>%
add_comments("Steepness is removed for technologies with maximum reduction rates of 0.") %>%
add_legacy_name("L201.nonghg_steepness_res") %>%
same_precursors_as(L201.nonghg_steepness) ->
L201.nonghg_steepness_res
L201.nonghg_res %>%
add_title("Pollutant emissions for energy resources in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take non-GHG emissions for the energy system, filter to include only resources") %>%
add_comments("in model base years, and rename to regional SO2.") %>%
add_legacy_name("L201.nonghg_res") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions",
"L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP") ->
L201.nonghg_res
# update into using input emissions + output driver
# YO Mar 2020
L201.ghg_res %>%
add_title("GHG emission factors from resource production in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take GHG emissions for resource production using EPA 2019 data") %>%
add_legacy_name("L201.ghg_res") %>%
add_precursors("common/GCAM_region_names",
"L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP") ->
L201.ghg_res
L201.ResReadInControl_nonghg_res %>%
add_title("Vintaging adjustments for pollutant emissions for energy resources") %>%
add_units("Tg/EJ") %>%
add_comments("Used to make per vintage adjustments to ensure overall emissions") %>%
add_comments("factors match the ones in L201.nonghg_res in historical years") %>%
same_precursors_as(L201.nonghg_res) ->
L201.ResReadInControl_nonghg_res
L201.ResReadInControl_ghg_res %>%
add_title("Vintaging adjustments for GHG emission factors from resource production") %>%
add_units("Tg/EJ") %>%
add_comments("Used to make per vintage adjustments to ensure overall emissions") %>%
add_comments("factors match the ones in L201.ghg_res in historical years") %>%
same_precursors_as(L201.ghg_res) ->
L201.ResReadInControl_ghg_res
return_data(L201.en_pol_emissions, L201.en_ghg_emissions, L201.en_bcoc_emissions, L201.OutputEmissions_elec, L201.nonghg_max_reduction, L201.nonghg_steepness, L201.nonghg_max_reduction_res, L201.nonghg_steepness_res, L201.nonghg_res, L201.ghg_res, L201.ResReadInControl_nonghg_res, L201.ResReadInControl_ghg_res)
} else {
stop("Unknown command")
}
}
bpbond/gcamdata documentation built on March 22, 2023, 4:52 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions module_emissions_L201.en_nonco2
Documented in module_emissions_L201.en_nonco2
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_emissions_L201.en_nonco2
#'
#' Generate non-CO2 emissions: pollutants, GHGs, non-CO2, BC/OCs, and reduction data.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{L201.en_pol_emissions}, \code{L201.en_ghg_emissions}, \code{L201.en_bcoc_emissions}, \code{L201.OutputEmissions_elec}, \code{L201.nonghg_max_reduction}, \code{L201.nonghg_steepness}, \code{L201.nonghg_max_reduction_res}, \code{L201.nonghg_steepness_res}, \code{L201.nonghg_res}, \code{L201.ghg_res}, \code{L201.ResReadInControl_nonghg_res}, \code{L201.ResReadInControl_ghg_res}. The corresponding file in the
#' original data system was \code{L201.en_nonco2.R} (emissions level2).
#' @details Set up all of the inputs needed for the energy system non-CO2 emissions in GCAM.
#' This includes historical emissions, drivers (input or output), and pollution controls.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter full_join left_join mutate pull select
#' @importFrom tidyr gather
#' @author BBL July 2017
module_emissions_L201.en_nonco2 <- function(command, ...) {
UCD_tech_map_name <- if_else(energy.TRAN_UCD_MODE == 'rev.mode', "energy/mappings/UCD_techs_revised", "energy/mappings/UCD_techs")
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "emissions/mappings/ind_subsector_revised",
FILE = "energy/A_regions",
"L111.nonghg_tg_R_en_S_F_Yh",
"L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L112.ghg_tg_R_en_S_F_Yh",
"L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L114.bcoc_tgej_R_en_S_F_2000",
"L151.nonghg_ctrl_R_en_S_T",
FILE = "emissions/A51.steepness",
"L244.DeleteThermalService",
# the following to be able to map in the input.name to
# use for the input-driver
FILE = "energy/calibrated_techs",
FILE = "energy/calibrated_techs_bld_det",
FILE = UCD_tech_map_name))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L201.en_pol_emissions",
"L201.en_ghg_emissions",
"L201.en_bcoc_emissions",
"L201.OutputEmissions_elec",
"L201.nonghg_max_reduction",
"L201.nonghg_steepness",
"L201.nonghg_max_reduction_res",
"L201.nonghg_steepness_res",
"L201.nonghg_res",
"L201.ghg_res",
"L201.ResReadInControl_nonghg_res",
"L201.ResReadInControl_ghg_res"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
year <- value <- supplysector <- region <- subsector <- subsector.emissions <- subsector.original<- stub.technology <- Non.CO2 <-
input.emissions <- `2000` <- emiss.coef <- ctrl.name <- max_reduction <- variable <-
steepness <- SO2 <- NOx <- CO <- BC <- OC <- NMVOC <- resource <- has_district_heat <-
. <- region <- supplysector <- max.reduction <- technology <- minicam.energy.input <-
tranSubsector <- tranTechnology <- input.name <- efficiency <- fuel <- subsector_orig <- NULL # silence package check notes
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A_regions <- get_data(all_data, "emissions/A_regions")
A_regions.en <- get_data(all_data, "energy/A_regions")
ind_subsector_revised <- get_data(all_data,"emissions/mappings/ind_subsector_revised")
L111.nonghg_tg_R_en_S_F_Yh <- get_data(all_data, "L111.nonghg_tg_R_en_S_F_Yh", strip_attributes = TRUE)
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP <- get_data(all_data, "L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP", strip_attributes = TRUE)
L112.ghg_tg_R_en_S_F_Yh <- get_data(all_data, "L112.ghg_tg_R_en_S_F_Yh", strip_attributes = TRUE)
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP <- get_data(all_data, "L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP", strip_attributes = TRUE)
L114.bcoc_tgej_R_en_S_F_2000 <- get_data(all_data, "L114.bcoc_tgej_R_en_S_F_2000", strip_attributes = TRUE)
L151.nonghg_ctrl_R_en_S_T <- get_data(all_data, "L151.nonghg_ctrl_R_en_S_T", strip_attributes = TRUE)
A51.steepness <- get_data(all_data, "emissions/A51.steepness", strip_attributes = TRUE)
L244.DeleteThermalService <- get_data(all_data, "L244.DeleteThermalService", strip_attributes = TRUE)
# make a complete mapping to be able to look up with sector + subsector + tech the
# input name to use for an input-driver
bind_rows(
get_data(all_data, "energy/calibrated_techs") %>% select(supplysector, subsector, fuel, technology, minicam.energy.input),
get_data(all_data, "energy/calibrated_techs_bld_det") %>% select(supplysector, subsector, fuel, technology, minicam.energy.input),
get_data(all_data, UCD_tech_map_name) %>% select(supplysector, subsector = tranSubsector, fuel, technology = tranTechnology, minicam.energy.input)) %>%
left_join(ind_subsector_revised %>% select(supplysector, subsector.emissions, fuel, technology, minicam.energy.input),
by=c("supplysector","fuel","technology","minicam.energy.input")) %>% #remap iron and steel subsector to match emissions data
mutate(subsector = if_else(!is.na(subsector.emissions),subsector.emissions,subsector)) %>%
select(-subsector.emissions)%>%
rename(stub.technology = technology,
input.name = minicam.energy.input) %>%
distinct() ->
EnTechInputNameMap
# L201.en_pol_emissions: Pollutant emissions for energy technologies in all regions
L111.nonghg_tg_R_en_S_F_Yh %>%
filter(supplysector != "out_resources",
year %in% emissions.MODEL_BASE_YEARS) %>%
# add region name and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(EnTechInputNameMap,by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, input.emissions = value, Non.CO2, input.name) %>%
mutate(input.emissions = signif(input.emissions, emissions.DIGITS_EMISSIONS)) ->
L201.en_pol_emissions
# L201.en_ghg_emissions: GHG emissions for energy technologies in all regions
L112.ghg_tg_R_en_S_F_Yh %>%
filter(supplysector != "out_resources",
year %in% emissions.MODEL_BASE_YEARS) %>%
# add region name and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(EnTechInputNameMap,by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, input.emissions = value, Non.CO2, input.name) %>%
mutate(input.emissions = signif(input.emissions, emissions.DIGITS_EMISSIONS)) ->
L201.en_ghg_emissions
# Add back in correct subsector name for iron and steel sector
L201.en_pol_emissions %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original, technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
L201.en_pol_emissions
L201.en_ghg_emissions %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original, technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
L201.en_ghg_emissions
EnTechInputNameMap %>%
left_join(ind_subsector_revised %>% select(supplysector,subsector.original,fuel,technology, minicam.energy.input) %>%
rename(stub.technology = technology,
input.name = minicam.energy.input),
by = c("supplysector", "fuel","stub.technology", "input.name")) %>%
mutate(subsector = if_else(!is.na(subsector.original),subsector.original,subsector)) %>%
select(-subsector.original) ->
EnTechInputNameMap
# L201.en_bcoc_emissions: BC/OC emissions factors for energy technologies in all regions
L114.bcoc_tgej_R_en_S_F_2000 %>%
filter(supplysector != "out_resources") %>%
# add region name, extend emissions factors across all base years, and round output
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
repeat_add_columns(tibble(year = MODEL_BASE_YEARS)) %>%
left_join_error_no_match(EnTechInputNameMap, by = c("supplysector", "subsector", "stub.technology")) %>%
select(region, supplysector, subsector, stub.technology, year, emiss.coef = `2000`, Non.CO2, input.name) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.en_bcoc_emissions
# Convert electricity to use output-driver instead. We do this, despite the addional hoops, because it makes it
# easier to swap out a different structure for electricity which requires pass-through technologies such as to
# add cooling technologies
# L201.OutputEmissions_elec: processing is straightforward here, just move electricity rows out of the InputEmissions
# table into the OutputEmissions
bind_rows(filter(L201.en_pol_emissions, supplysector == "electricity"),
filter(L201.en_ghg_emissions, supplysector == "electricity")) %>%
select(LEVEL2_DATA_NAMES[["OutputEmissions"]]) ->
L201.OutputEmissions_elec
L201.en_pol_emissions <- filter(L201.en_pol_emissions, supplysector != "electricity")
L201.en_ghg_emissions <- filter(L201.en_ghg_emissions, supplysector != "electricity")
L201.en_bcoc_emissions <- filter(L201.en_bcoc_emissions, supplysector != "electricity")
# L201.nonghg_max_reduction: maximum reduction for energy technologies in all regions
L151.nonghg_ctrl_R_en_S_T %>%
filter(supplysector != "out_resources") %>%
# add region name
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
select(-year)->L201.max_reduction
L201.max_reduction %>%
# select only certain columns in preparation for join below
select(region, supplysector, subsector, stub.technology, Non.CO2) %>%
mutate(year = emissions.CTRL_BASE_YEAR, ctrl.name = "GDP_control") %>%
left_join_error_no_match(L201.max_reduction,
by = c("region", "supplysector", "subsector", "stub.technology", "Non.CO2")) %>%
na.omit %>%
select(region, supplysector, subsector, stub.technology, year, Non.CO2, ctrl.name, max_reduction) ->
L201.nonghg_max_reduction
# L201.nonghg_steepness: steepness of reduction for energy technologies in all regions
A51.steepness %>%
gather(variable, steepness, SO2, NOx, CO, BC, OC, NMVOC) %>%
filter(supplysector != "out_resources") %>%
# extend steepness factors across all regions
repeat_add_columns(tibble(region = GCAM_region_names$region)) ->
L201.steepness
L201.nonghg_max_reduction %>%
mutate(year = emissions.CTRL_BASE_YEAR, ctrl.name = "GDP_control") %>%
left_join(L201.steepness,
by = c("region", "supplysector", "subsector", "stub.technology", "Non.CO2" = "variable")) %>%
na.omit %>%
select(region, supplysector, subsector, stub.technology, year, Non.CO2, ctrl.name, steepness) ->
L201.nonghg_steepness
# Remove rows where we only have a value for one of max.reduction or steepness
# TODO: is this what we want or should we raise an error? [from original code]
L201.nonghg_max_reduction %>%
full_join(L201.nonghg_steepness,
by = c("region", "supplysector", "subsector", "stub.technology", "year", "Non.CO2", "ctrl.name")) %>%
na.omit %>%
# No need to include a GDP control when the max.reduction is zero
filter(max_reduction > 0) ->
L201.nonghg_gdp_control
# remap iron and steel back to correct subsector, because fuel information is now attached
L201.nonghg_gdp_control %>%
left_join(EnTechInputNameMap %>% filter(supplysector == "iron and steel") %>% select(-input.name) %>%
rename(subsector_orig = subsector) %>% unique(),
by = c("supplysector", "stub.technology")) %>%
mutate(subsector = if_else(supplysector == "iron and steel", subsector_orig, subsector)) %>%
select(-subsector_orig) ->
L201.nonghg_gdp_control
L201.nonghg_max_reduction <- select(L201.nonghg_gdp_control, -steepness)
L201.nonghg_steepness <- select(L201.nonghg_gdp_control, -max_reduction)
# L201.nonghg_res: Pollutant emissions for energy resources in all regions
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
filter(supplysector == "out_resources",
year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector) %>%
rename(subresource = subsector, technology = stub.technology, emiss.coef = value) %>%
select(LEVEL2_DATA_NAMES[["ResEmissCoef"]]) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.nonghg_res
# L201.ghg_res: GHG emissions from resource production in all regions
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
filter(supplysector == "out_resources",
year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector) %>%
rename(subresource = subsector, technology = stub.technology, emiss.coef = value) %>%
select(LEVEL2_DATA_NAMES[["ResEmissCoef"]]) %>%
mutate(emiss.coef = signif(emiss.coef, emissions.DIGITS_EMISSIONS)) ->
L201.ghg_res
# Resources have vintaging going on in the historical years.
# The above emissions coefficients are the coefficients across vintages
# in the given model year. The best way to ensure the correct "total"
# emissions factor across vintages is realized is to use the ReadInControl
# to change the coefficients by vintage for all vintages. Note given the way
# the C++ operates we need to read in the "base" EmissCoef table and then the
# same values in the ReadInControl table all read into the first model period
# vintage. We will also need to "fillout" the value in the final calibration
# to the future model periods otherwise the vintage would revert back to the
# value in the EmissCoef table. Finally to turn "off" any adjustments made to
# new vintages in future model periods we must have ReadInControl with values of
# zero starting in the first future model period.
# L201.ResReadInControl_nonghg_res: Vintage adjustments for Pollutant emissions for energy resources in all regions
L201.nonghg_res %>%
# copy the final historical year value to the future model periods
bind_rows(L201.nonghg_res %>%
filter(year == MODEL_FINAL_BASE_YEAR) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS))) %>%
rename(future.emiss.coeff.year = year) %>%
mutate(year = MODEL_BASE_YEARS[1],
future.emiss.coeff.name = "vintage_adjust") %>%
select(LEVEL2_DATA_NAMES[["ResReadInControl"]]) ->
L201.ResReadInControl_nonghg_res
# turn "off" vintage adjustments for future year vintages
L201.ResReadInControl_nonghg_res %>%
mutate(year = MODEL_FUTURE_YEARS[1],
emiss.coef = 0.0) %>%
bind_rows(L201.ResReadInControl_nonghg_res) ->
L201.ResReadInControl_nonghg_res
# L201.ResReadInControl_ghg_res: Vintage adjustments for GHG emissions from resource production in all regions
L201.ghg_res %>%
# copy the final historical year value to the future model periods
bind_rows(L201.ghg_res %>%
filter(year == MODEL_FINAL_BASE_YEAR) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS))) %>%
rename(future.emiss.coeff.year = year) %>%
mutate(year = MODEL_BASE_YEARS[1],
future.emiss.coeff.name = "vintage_adjust") %>%
select(LEVEL2_DATA_NAMES[["ResReadInControl"]]) ->
L201.ResReadInControl_ghg_res
# turn "off" vintage adjustments for future year vintages
L201.ResReadInControl_ghg_res %>%
mutate(year = MODEL_FUTURE_YEARS[1],
emiss.coef = 0.0) %>%
bind_rows(L201.ResReadInControl_ghg_res) ->
L201.ResReadInControl_ghg_res
# L201.nonghg_max_reduction_res: maximum reduction for resources in all regions
L151.nonghg_ctrl_R_en_S_T %>%
filter(supplysector == "out_resources") %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(resource = subsector,
year = emissions.GHG_CONTROL_READIN_YEAR,
ctrl.name = "GDP_control") %>%
rename(subresource = subsector, technology = stub.technology, max.reduction = max_reduction) %>%
select(LEVEL2_DATA_NAMES[["GDPCtrlMaxRes"]]) ->
L201.nonghg_max_reduction_res
# L201.nonghg_steepness_res: steepness of reduction for resources in all regions
A51.steepness %>%
gather(Non.CO2, value, SO2, NOx, CO, BC, OC, NMVOC) %>%
filter(supplysector == "out_resources") %>%
# extend steepness factors across all regions
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(resource = subsector,
year = emissions.GHG_CONTROL_READIN_YEAR,
ctrl.name = "GDP_control") %>%
rename(subresource = subsector, technology = stub.technology, steepness = value) %>%
select(LEVEL2_DATA_NAMES[["GDPCtrlSteepRes"]]) ->
L201.nonghg_steepness_res
# Remove rows where we only have a value for one of max.reduction or steepness
# TODO: is this what we want or should we raise an error?
L201.nonghg_max_reduction_res %>%
full_join(L201.nonghg_steepness_res, by = c("region", "resource", "subresource", "technology", "year", "Non.CO2", "ctrl.name")) %>%
na.omit %>%
# No need to include a GDP control when the max.reduction is zero
filter(max.reduction > 0) ->
L201.nonghg_gdp_control_res
L201.nonghg_max_reduction_res <- select(L201.nonghg_gdp_control_res, -steepness)
L201.nonghg_steepness_res <- select(L201.nonghg_gdp_control_res, -max.reduction)
# Rename to regional SO2
L201.en_pol_emissions <- rename_SO2(L201.en_pol_emissions, A_regions, FALSE)
L201.OutputEmissions_elec <- rename_SO2(L201.OutputEmissions_elec, A_regions, FALSE)
L201.nonghg_max_reduction <- rename_SO2(L201.nonghg_max_reduction, A_regions, FALSE)
L201.nonghg_steepness <- rename_SO2(L201.nonghg_steepness, A_regions, FALSE)
L201.nonghg_res <- rename_SO2(L201.nonghg_res, A_regions, FALSE)
L201.ResReadInControl_nonghg_res <- rename_SO2(L201.ResReadInControl_nonghg_res, A_regions, FALSE)
L201.nonghg_steepness_res <- rename_SO2(L201.nonghg_steepness_res, A_regions, FALSE)
L201.nonghg_max_reduction_res <- rename_SO2(L201.nonghg_max_reduction_res, A_regions, FALSE)
# Remove district heat from regions that do have have it
A_regions.en %>%
filter(has_district_heat == 1) %>%
pull(region) ->
distheat.regions
L201.en_pol_emissions <- filter(L201.en_pol_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.en_ghg_emissions <- filter(L201.en_ghg_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.en_bcoc_emissions <- filter(L201.en_bcoc_emissions, supplysector != "district heat" | region %in% distheat.regions)
L201.nonghg_max_reduction <- filter(L201.nonghg_max_reduction, supplysector != "district heat" | region %in% distheat.regions)
L201.nonghg_steepness <- filter(L201.nonghg_steepness, supplysector != "district heat" | region %in% distheat.regions)
# It may be the case with certain regional aggregations that regions exist that have no
# heating or cooling sectors. We should delete those here.
# Delete sectors that do not exist due to zero heating/cooling degree days
delete_nonexistent_sectors <- function(x, L201.delete.sectors) {
filter(x, ! paste0(region, supplysector) %in% L201.delete.sectors)
}
L201.delete.sectors <- paste0(L244.DeleteThermalService$region, L244.DeleteThermalService$supplysector)
L201.en_pol_emissions <- delete_nonexistent_sectors(L201.en_pol_emissions, L201.delete.sectors)
L201.en_ghg_emissions <- delete_nonexistent_sectors(L201.en_ghg_emissions, L201.delete.sectors)
L201.en_bcoc_emissions <- delete_nonexistent_sectors(L201.en_bcoc_emissions, L201.delete.sectors)
L201.nonghg_max_reduction <- delete_nonexistent_sectors(L201.nonghg_max_reduction, L201.delete.sectors)
L201.nonghg_steepness <- delete_nonexistent_sectors(L201.nonghg_steepness, L201.delete.sectors)
# Produce outputs
L201.en_pol_emissions %>%
add_title("Pollutant emissions for energy technologies in all regions") %>%
add_units("Tg") %>%
add_comments("Take non-GHG emissions for the energy system, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_pol_emissions") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L111.nonghg_tg_R_en_S_F_Yh",
"L244.DeleteThermalService",
"emissions/mappings/ind_subsector_revised") ->
L201.en_pol_emissions
L201.en_ghg_emissions %>%
add_title("GHG emissions for energy technologies in all regions") %>%
add_units("Tg") %>%
add_comments("Take GHG emissions for the energy system, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_ghg_emissions") %>%
add_precursors("common/GCAM_region_names",
"energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L112.ghg_tg_R_en_S_F_Yh",
"L244.DeleteThermalService",
"emissions/mappings/ind_subsector_revised") ->
L201.en_ghg_emissions
L201.en_bcoc_emissions %>%
add_title("BC/OC emissions factors for energy technologies in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take BC/OC emissions factors for energy technologies, filter out resources") %>%
add_comments("in model base years, rename to regional SO2, filter to district heat, ") %>%
add_comments("and delete sectors with zero heating and zero cooling degree days.") %>%
add_legacy_name("L201.en_bcoc_emissions") %>%
add_precursors("common/GCAM_region_names",
"energy/A_regions",
"energy/calibrated_techs",
"energy/calibrated_techs_bld_det",
UCD_tech_map_name,
"L114.bcoc_tgej_R_en_S_F_2000",
"L244.DeleteThermalService") ->
L201.en_bcoc_emissions
L201.OutputEmissions_elec %>%
add_title("GHG and pollutant emissions for the electricity sector") %>%
add_units("Tg") %>%
add_comments("We've seperated electricity out to be driven by output-driver so we") %>%
add_comments("more easily re-configure the strucutre of the sector to swap in cooling") %>%
add_comments("technology choice which is implemented with pass-through sector/tech") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L111.nonghg_tg_R_en_S_F_Yh") ->
L201.OutputEmissions_elec
L201.nonghg_max_reduction %>%
rename(max.reduction = max_reduction) %>% # no idea why old data system renamed this
add_title("Maximum emissions reduction rates for energy technologies in all regions") %>%
add_units("%") %>%
add_comments("The maximum reduction is calculated in L151 to match the maximum emissions controls assumed in GCAM3.") %>%
add_comments("Controls are removed when the maximum reduction is zero.") %>%
add_legacy_name("L201.nonghg_max_reduction") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L151.nonghg_ctrl_R_en_S_T",
"L244.DeleteThermalService") ->
L201.nonghg_max_reduction
L201.nonghg_steepness %>%
add_title("Steepness of emissions reduction for energy technologies in all regions") %>%
add_units("%") %>%
add_comments("The steepness is from an assumptions file (A51_steepness). It was chosen to replicate the pollutant reduction rates for SO2 in GCAM3.") %>%
add_comments("Steepness is removed for technologies with maximum reduction rates of 0.") %>%
add_legacy_name("L201.nonghg_steepness") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions", "energy/A_regions",
"L151.nonghg_ctrl_R_en_S_T",
"emissions/A51.steepness",
"L244.DeleteThermalService") ->
L201.nonghg_steepness
L201.nonghg_max_reduction_res %>%
add_title("Maximum reduction for resources in all regions") %>%
add_units("%") %>%
add_comments("The maximum reduction is calculated in L151 to match the maximum emissions controls assumed in GCAM3.") %>%
add_comments("Controls are removed when the maximum reduction is zero.") %>%
add_legacy_name("L201.nonghg_max_reduction_res") %>%
same_precursors_as(L201.nonghg_max_reduction) ->
L201.nonghg_max_reduction_res
L201.nonghg_steepness_res %>%
add_title("Steepness of reduction for resources in all regions") %>%
add_units("%") %>%
add_comments("The steepness is from an assumptions file (A51_steepness). It was chosen to replicate the pollutant reduction rates for SO2 in GCAM3.") %>%
add_comments("Steepness is removed for technologies with maximum reduction rates of 0.") %>%
add_legacy_name("L201.nonghg_steepness_res") %>%
same_precursors_as(L201.nonghg_steepness) ->
L201.nonghg_steepness_res
L201.nonghg_res %>%
add_title("Pollutant emissions for energy resources in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take non-GHG emissions for the energy system, filter to include only resources") %>%
add_comments("in model base years, and rename to regional SO2.") %>%
add_legacy_name("L201.nonghg_res") %>%
add_precursors("common/GCAM_region_names",
"emissions/A_regions",
"L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP") ->
L201.nonghg_res
# update into using input emissions + output driver
# YO Mar 2020
L201.ghg_res %>%
add_title("GHG emission factors from resource production in all regions") %>%
add_units("Tg/EJ") %>%
add_comments("Take GHG emissions for resource production using EPA 2019 data") %>%
add_legacy_name("L201.ghg_res") %>%
add_precursors("common/GCAM_region_names",
"L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP") ->
L201.ghg_res
L201.ResReadInControl_nonghg_res %>%
add_title("Vintaging adjustments for pollutant emissions for energy resources") %>%
add_units("Tg/EJ") %>%
add_comments("Used to make per vintage adjustments to ensure overall emissions") %>%
add_comments("factors match the ones in L201.nonghg_res in historical years") %>%
same_precursors_as(L201.nonghg_res) ->
L201.ResReadInControl_nonghg_res
L201.ResReadInControl_ghg_res %>%
add_title("Vintaging adjustments for GHG emission factors from resource production") %>%
add_units("Tg/EJ") %>%
add_comments("Used to make per vintage adjustments to ensure overall emissions") %>%
add_comments("factors match the ones in L201.ghg_res in historical years") %>%
same_precursors_as(L201.ghg_res) ->
L201.ResReadInControl_ghg_res
return_data(L201.en_pol_emissions, L201.en_ghg_emissions, L201.en_bcoc_emissions, L201.OutputEmissions_elec, L201.nonghg_max_reduction, L201.nonghg_steepness, L201.nonghg_max_reduction_res, L201.nonghg_steepness_res, L201.nonghg_res, L201.ghg_res, L201.ResReadInControl_nonghg_res, L201.ResReadInControl_ghg_res)
} else {
stop("Unknown command")
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.